Hadoop based Efficient Product Recommendation System in Online Web Dr. Saravanan K.*, Dr. Sargunam S. Silas**, Dr. Rajaram M.*** *Assistant Professor, Department of Computer Science and Engineering, Anna University, Regional Campus, Tirunelveli, Tamilnadu, India **Assistant Professor, Department of Management Studies, Anna University, Regional Campus, Tirunelveli, Tamilnadu, India ***Vice Chancellor, Anna University, Chennai, Tamilnadu, India Online published on 2 August, 2016. Abstract Existing product recommendation system in the online shop websites allows the user to choose the products in the available stocks and render comparison within their products. Commonly these systems use super computers for data processing which is not cost efficient. Thereby limiting the users to analyze before buying a product and also at the same time it suffers from big data problem as data generation has become more powerful that capturing, managing and processing of data is becoming very complex. Hence, we propose an efficient and precise service comparison and recommender system which enables the shoppers to deeply analyze on what product to choose and in which application easily and fairly using Hadoop framework which allow multiple nodes to obtain the data and perform parallel processing for efficient computation and provides a single gateway to all service providers. Top Keywords Big data, product recommendation, online ecommerce, hadoop, shopping. Top |